Search Results (97)

Accurately estimating the radiation dose received by an individual is essential for evaluating potential damage caused by exposure to ionizing radiation. Most retrospective dosimetry methods require the time since exposure to be known and rely on calibration curves specific to that time point. In this work, we introduce a novel method tailored to the γ-H2AX assay, which is a protein-based biomarker for radiation exposure, that enables the estimation of both the radiation dose and the time of exposure within a plausible post-exposure interval. Specifically, we extend calibration curves available at two distinct time points by incorporating the biological decay of foci, resulting in a model that captures the joint dependence of foci count on both dose and time. We demonstrate the applicability of this approach using both real-world and simulated data. Full article

The results of radiotherapy in patients with primary malignant brain tumors are extremely dissatisfactory: the overall survival after a diagnosis of glioblastoma is typically less than three years. The development of spatially fractionated radiotherapy techniques could help to improve this bleak prognosis. In order to develop technical equipment and organ-specific therapy plans, dosimetry studies as well as radiobiology studies are conducted. Although perfect spheres are considered optimal phantoms by physicists, this does not reflect the wide variety of head sizes and shapes in our patient community. Depth from surface and X-ray dose absorption by tissue between dose entry point and target, two key parameters in medical physics planning, are largely determined by the shape and thickness of the skull bone. We have, therefore, designed and produced a biomimetic tool to correlate measured technical dose and biological response in human cancer cells: a brain phantom, produced from tissue-equivalent materials. In a first pilot study, utilizing our phantom to correlate technical dose measurements and metabolic response to radiation in human cancer cell lines, we demonstrate why an anthropomorphic phantom is preferable over a simple spheroid phantom. Full article

Human exposure to micro- and nanoplastic (MNP) has become an increasing concern due to its accumulation in the environment and human body. In the human organism, MNP accumulates in various tissues, including the central nervous system, where it is associated which neurotoxic effects. Beyond its inherent toxicity, MNP also acts as a carrier for various chemical contaminants, including metals. Consequently, recent studies emphasize the importance of the evaluation of co-exposure scenarios involving MNP and other types of nanoparticles. In this study, we investigated effects of co-exposure to 20 nm silver nanoparticles (AgNPs) and 20 nm polystyrene nanoparticles (PSNPs) on cell viability and the expression of inflammation-related long non-coding RNAs (lncRNAs) in undifferentiated and differentiated Lund human mesencephalic (LUHMES) cells. While PSNPs alone did not significantly affect cell viability or lncRNA expression, AgNPs markedly reduced viability and deregulated lncRNA expression in both cell types. Notably, in differentiated cells, co-exposure to AgNPs and high concentrations of PSNPs led to a significantly greater reduction in viability compared to AgNPs alone, suggesting a synergistic effect. At the molecular level, both synergistic and antagonistic interactions between AgNPs and PSNPs were observed in the regulation of lncRNA expression, depending on the cell differentiation status. These findings highlight the complex biological interactions between AgNPs and PSNPs and emphasize the importance of considering nanoparticle co-exposures in toxicological evaluations, as combined exposures may significantly affect cellular and molecular responses. Full article

Next-generation sequencing (NGS) has been well applied to assess genetic abnormalities in various biological samples to investigate disease mechanisms. With the advent of high-throughput and automatic testing platforms, NGS can identify radiation-sensitive and dose-responsive biomarkers, contributing to triage patients and determining risk groups for treatment in a nuclear emergency. While bulk NGS provides a snapshot of the average gene expression or genomic changes within a group of cells after the radiation, it cannot provide information on individual cells within the population. On the other hand, single-cell sequencing involves isolating individual cells and sequencing the genetic material from each cell separately. This approach allows for the identification of gene expression and genomic changes in individual cells, providing a high-resolution view of cellular diversity and heterogeneity within a sample. Single-cell sequencing is particularly useful to identify cell-specific features of dose-response and organ-response genes. While single-cell RNA sequencing (scRNA-seq) technology is still emerging in radiation research, it holds significant promise for identifying biomarkers related to radiation exposure and tailoring post-radiation medical care. This review aims to focus on current methods of radiation dosimetry and recently identified biomarkers associated with radiation exposure. Additionally, it addresses the development of NGS techniques in the context of radiation situations, such as cancer treatment and emergency events, with a particular emphasis on single-cell sequencing technology. Full article

Internalization of nanoparticles (NPs), including nanoplastic, is one of the key factors determining their toxicity. In this work, we studied the toxicity and mechanisms of the uptake of model fluorescent polystyrene NPs (PS NPs) of three different sizes (30, 50, and 100 nm) in three human cancer cells lines; two originated from gut tissue (HT-29 and Caco-2) and one originated from liver tissue (Hep G2). Toxicity was measured by Neutral Red Assay (NRU), whereas mechanisms of uptake were studied using flow cytometry and different uptake inhibitors. The toxicity of the studied NPs followed a general rule observed for NPs—the smaller ones were more toxic than the larger ones. This relationship was dose dependent; however, the overall toxicity of the studied NPs was very low, despite the significant uptake of PS NPs. Although clathrin- and caveolin-dependent uptake is generally accepted as a major route of NP uptake, the inhibition of both mechanisms did not affect PS NP uptake in the cell lines studied in this work. Further experiments revealed that the major route of PS NP uptake in these cells is a scavenger receptor-mediated uptake. Full article

Nanomaterials represent an innovation in cancer imaging by offering enhanced contrast, improved targeting capabilities, and multifunctional imaging modalities. Recent advancements in material engineering have enabled the development of nanoparticles tailored for various imaging techniques, including magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), and ultrasound (US). These nanoscale agents improve sensitivity and specificity, enabling early cancer detection and precise tumor characterization. Monte Carlo (MC) simulations play a pivotal role in optimizing nanomaterial-based imaging by modeling their interactions with biological tissues, predicting contrast enhancement, and refining dosimetry for radiation-based imaging techniques. These computational methods provide valuable insights into nanoparticle behavior, aiding in the design of more effective imaging agents. Moreover, artificial intelligence (AI) and machine learning (ML) approaches are transforming cancer imaging by enhancing image reconstruction, automating segmentation, and improving diagnostic accuracy. AI-driven models can also optimize MC-based simulations by accelerating data analysis and refining nanoparticle design through predictive modeling. This review explores the latest advancements in nanomaterial-based cancer imaging, highlighting the synergy between nanotechnology, MC simulations, and AI-driven innovations. By integrating these interdisciplinary approaches, future cancer imaging technologies can achieve unprecedented precision, paving the way for more effective diagnostics and personalized treatment strategies. Full article

Multiwalled carbon nanotubes (MWCNTs) are used in many areas of industry and medicine. However, there is evidence suggesting profibrogenic action of MWCNTs, probably via the epithelial–mesenchymal transition mechanism (EMT). The aim of this study was to evaluate the prometastatic activity of 5–20 nm and 50–80 nm MWCNTs against cells of the MDA-MB-436 line. We used MTT and NR assays to determine MWCNTs’ cytotoxicity and the level of malonylodialdehyde and thiol compounds as indicators of oxidative stress. qRT-PCR was used to examine the expression of EMT markers. The QCM Chemotaxis Cell Migration Assay was used to assess cell migration, while the Cytokine Array Kit and Apoptosis Array Kit were used to determine cytokine expression and induction of apoptosis. The interleukin 6, C-X-C motif chemokine ligand 8, and tumor growth factor beta 1 (TGFB1) secretion was determined by ELISA. MWCNTs were toxic to MDA-MB-436 cells and induced cell death via the apoptosis pathway. MWCNTs induced a low level of oxidative stress and were associated with increased secretion of pro-inflammatory cytokines and chemokines, including proteins important in breast cancer metastasis. Cells incubated with MWCNTs showed increased expression of mesenchymal EMT markers. However, in contrast to these results, the migration of MWCNT-treated cells increased only modestly relative to untreated cells. Also, the secretion of TGFB1, a key inducer and regulator of EMT, increased only slightly. In summary, the multifaceted effect of MWCNTs on cancer cells encourages further work on the safety of nanomaterials. Full article

Nicotinic acetylcholine receptor (α7-nAChR) plays a crucial role in cognitive functions like memory and attention. Positron emission tomography (PET) imaging of α7-nAChR is gaining attraction for understanding and monitoring central nervous system disorders, such as Alzheimer’s disease, Parkinson’s disease, and schizophrenia. We developed [¹¹C]KIn83, a novel α7-nAChR radioligand, and evaluated its biological properties. This study focused on two objectives: (1) to validate its Good Manufacturing Practice (GMP)-compliant production, and (2) to assess the dosimetry of [¹¹C]KIn83 using non-human primate (NHP) whole-body PET data. Radiolabeling and drug product delivery of [¹¹C]KIn83 were conducted using an automated synthesis module within a controlled GMP environment. The quality control tests performed adhered to the European Pharmacopoeia guidelines. The production of [¹¹C]KIn83 was validated according to GMP standards, encompassing automated synthesis and quality control measures. For the dosimetry assessment, two female cynomolgus monkeys underwent whole-body PET scans. The radioactivity values injected for [¹¹C]KIn83 were 150 MBq and 155 MBq, respectively, with an estimated radiation dose of 0.0047 mSv/MBq. Our findings pave the way for future clinical studies that investigate the potential of [¹¹C]KIn83 to measure α7-nAChR, aiding our understanding and possibly supporting diagnoses of different cognitive disorders. Full article

Monte Carlo (MC) simulations have become important in advancing nanoparticle (NP)-based applications for cancer imaging and therapy. This review explores the critical role of MC simulations in modeling complex biological interactions, optimizing NP designs, and enhancing the precision of therapeutic and diagnostic strategies. Key findings highlight the ability of MC simulations to predict NP bio-distribution, radiation dosimetry, and treatment efficacy, providing a robust framework for addressing the stochastic nature of biological systems. Despite their contributions, MC simulations face challenges such as modeling biological complexity, computational demands, and the scarcity of reliable nanoscale data. However, emerging technologies, including hybrid modeling approaches, high-performance computing, and quantum simulation, are poised to overcome these limitations. Furthermore, novel advancements such as FLASH radiotherapy, multifunctional NPs, and patient-specific data integration are expanding the capabilities and clinical relevance of MC simulations. This topical review underscores the transformative potential of MC simulations in bridging fundamental research and clinical translation. By facilitating personalized nanomedicine and streamlining regulatory and clinical trial processes, MC simulations offer a pathway toward more effective, tailored, and accessible cancer treatments. The continued evolution of simulation techniques, driven by interdisciplinary collaboration and technological innovation, ensures that MC simulations will remain at the forefront of nanomedicine’s progress. Full article

Telomere shortening has been linked to type 2 diabetes (T2D) and its complications. This study aims to determine whether leukocyte telomere length (LTL) could be a useful marker in predicting the onset of complications in patients suffering from T2D. Enrolled study subjects were 147 T2D patients. LTL was measured using a quantitative PCR method. Key subject’s demographics and other clinical characteristics were also included. T2D patients with the shortest LTL had higher TC and non-HDL levels, compared to subjects with the longest LTL (p = 0.013). Also, T2D patients suffering from diabetic nephropathy showed significant differences in LDL levels (p = 0.023). While in the group of T2D patients with diabetic retinopathy, significant differences were observed for parameters, such as duration of diabetes (p = 0.043), HbA1c (p = 0.041), TC (p = 0.003), LDL (p = 0.015), Non-HDL (p = 0.004) and TG (p = 0.045). Logistic regression analysis confirmed a significant risk of association of TC and Non-HDL levels with LTL in the 3rd tertile LTL for the crude model adjusted for sex and age, with respective odds ratios of 0.71 (95% CI 0.56–0.91) and 0.73 (95% CI 0.58–0.91). No significant associations were found between LTL in T2D patients and the prevalence of common T2D complications. Nevertheless, a significant association was demonstrated between LTL and some markers of dyslipidemia, including in T2D patients with either diabetic nephropathy or retinopathy. Therefore, analysis of LTL in T2D patients’ leukocytes demonstrates a promising potential as a marker in predicting the onset of complications in T2D. This could also help in establishing an effective treatment strategy or even prevent and delay the onset of these severe complications. Full article

Photobiomodulation (PBM) therapy, a therapeutic approach utilizing low-level light, has garnered significant attention for its potential to modulate various biological processes. This study aimed at optimizing and investigating the effects of PBM on angiogenesis and mitochondrial metabolic activity. In vitro experiments using human umbilical vein endothelial cells (HUVECs) and vascular smooth muscle cells (VSMCs) were performed to assess PBM’s impacts on cell migration, proliferation, endogenous protoporphyrin IX production, mitochondrial membrane potential, Rhodamine 123 fluorescence lifetime, mitochondrial morphology, and oxygen consumption. Our findings demonstrated that the PBM approach significantly stimulates HUVECs and VSMCs, highlighting the importance of precise light dosimetry for optimal outcomes. Interestingly, our results indicate that in our conditions, the optimal radiometric and spectral parameters are similar for HUVECs and VSMCs for the different endpoints mentioned above. In conclusion, our study strongly suggests that PBM holds promise as a therapeutic intervention for conditions characterized by impaired angiogenesis, such as wound healing, ischemia, and cardiovascular disease. Further research is necessary to fully elucidate the underlying mechanisms and optimize the radiometric and spectral parameters for clinical applications. Full article

The rapid development of nanotechnology during the last two decades has created new opportunities to design and generate more advanced nanotheranostics with diversified capabilities for diagnosis, drug delivery, and treatment response monitoring in a single platform. To date, several approaches have been employed in order to develop nanotheranostics. The purpose of this review is to briefly discuss the key components of nanotheranostic systems, to present the conventional and upcoming imaging and therapeutic modalities that employ nanotheranostic systems, and to evaluate recent progress in the field of cancer nanotheranostic systems in the past five years (2020–2024). Special attention is focused on the design of cancer nanotheranostic systems, their composition, specificity, potential for multimodal imaging and therapy, and in vitro and in vivo characterization. Full article

The Dicentric Chromosome Assay (DCA) is widely used in biological dosimetry, where the number of dicentric chromosomes induced by ionizing radiation (IR) exposure is quantified to estimate the absorbed radiation dose an individual has received. Dicentric chromosome scoring is a laborious and time-consuming process which is performed manually in most cytogenetic biodosimetry laboratories. Further, dicentric chromosome scoring constitutes a bottleneck when several hundreds of samples need to be analyzed for dose estimation in the aftermath of large-scale radiological/nuclear incident(s). Recently, much interest has focused on automating dicentric chromosome scoring using Artificial Intelligence (AI) tools to reduce analysis time and improve the accuracy of dicentric chromosome detection. Our study aims to detect dicentric chromosomes in metaphase plate images using an ensemble of artificial neural network detectors suitable for datasets that present a low number of samples (in this work, only 50 images). In our approach, the input image is first processed by several operators, each producing a transformed image. Then, each transformed image is transferred to a specific detector trained with a training set processed by the same operator that transformed the image. Following this, the detectors provide their predictions about the detected chromosomes. Finally, all predictions are combined using a consensus function. Regarding the operators used, images were binarized separately applying Otsu and Spline techniques, while morphological opening and closing filters with different sizes were used to eliminate noise, isolate specific components, and enhance the structures of interest (chromosomes) within the image. Consensus-based decisions are typically more precise than those made by individual networks, as the consensus method can rectify certain misclassifications, assuming that individual network results are correct. The results indicate that our methodology worked satisfactorily in detecting a majority of chromosomes, with remarkable classification performance even with the low number of training samples utilized. AI-based dicentric chromosome detection will be beneficial for a rapid triage by improving the detection of dicentric chromosomes and thereby the dose prediction accuracy. Full article

Monte Carlo techniques have been extensively used for planning laser-based clinical procedures such as photobiomodulation. However, the effects of several biological tissue characteristics regarding its morphological structure and physiological parameters have not been carefully addressed in many applications. Specifically, many questions remain concerning the effect of skin phototype and body mass index on the effectiveness of photobiomodulation for extraoral therapies. To address these questions, a Monte Carlo simulation model of the effects of body mass index-dependent skin structure on different Fitzpatrick skin types was developed, specifically tailored for the morphological characteristics of cheek tissue. The model describes the settings of a typical oral photobiomodulation treatment protocol for pain relief, namely the use of 660 nm and 808 nm laser wavelengths and a therapeutic dose of $2.0{\mathrm{J}/\mathrm{cm}}^2$ on the masseter muscle. The simulations were used to train a machine learning predictive model aimed at accelerating the treatment planning stage and assessing the importance of patient-specific parameters. A multiple-regression approach was adopted to predict muscle dose and treatment time for effective delivered dose. Body mass index had little effect on epidermal energy deposition, but an important impact on muscle dose parameters. Phototype also influenced muscle dose, but to a lesser extent than body mass index. The results of this study can be used to develop customized dosimetry phototherapy protocols to promote more effective and safe clinical outcomes. Full article

Cancer is the second leading cause of death worldwide. Around half of all cancer patients undergo some type of radiation therapy throughout the course of their treatment. Photon radiation remains (RT) the most widely utilized modality of radiotherapy despite recent advancements in proton radiation therapy (PBT). PBT makes use of the particle’s biological property known as the Bragg peak to better spare healthy tissue from radiation damage, with data to support that this treatment modality is less toxic than photon RT. Hence, proton radiation dosimetry looks better compared to photon dosimetry; however, due to proton-specific uncertainties, unexpected acute, subacute, and long-term toxicities can be encountered. Reported neurotoxicity resulting from proton radiation treatments include radiation necrosis, moyamoya syndrome, neurosensory toxicities, brain edema, neuromuscular toxicities, and neurocognitive toxicities. Pulmonary toxicities include pneumonitis and fibrosis, pleural effusions, and bronchial toxicities. Pericarditis, pericardial effusions, and atrial fibrillations are among the cardiac toxicities related to proton therapy. Gastrointestinal and hematological toxicities are also found in the literature. Genitourinary toxicities include urinary and reproductive-related toxicities. Osteological, oral, endocrine, and skin toxicities have also been reported. The side effects will be comparable to the ones following photon RT, nonetheless at an expected lower incidence. The toxicities collected mainly from case reports and clinical trials are described based on the organs affected and functions altered. Full article